Ann BYKERK-KAUFFMAN, Ronald K. MATHENEY, Matthew NYMAN, David McCONNELL, Matthew NYMAN, David McCONNELL, Jennifer A. STEMPIEN, David A. BUDD, Lisa GILBERT, Megan JONES, Catharine KNIGHT, Katrien KRAFT, Ryan NELL, Dexter PERKINS, Rachel TEASDALE, Tatiana VISLOVA, and Karl R. WIRTH The Effect of Student Motivation and Learning Strategies on Performance in Physical Geology Courses: GARNET Part 4, Student Performance

How do students’ values, motivations, expectations, and study strategies affect their performance in our classes? GARNET: Geoscience Affective Research Network

Motivated Strategies for Learning Questionnaire (81 questions) CategoriesSubcategoriesSubscales (# of questions) Motivation Scales Value Intrinsic goal orientation (4) Extrinsic goal orientation (4) Task value (6) Expectancy Control of learning beliefs (4) Self-efficacy (8) AffectTest anxiety (5) Cognitive Scales Cognitive strategies Rehearsal (4) Elaboration (6) Organization (4) Critical thinking (5) Metacognitive strategiesMetacognition (12) Resource Management Time & study environment (8) Effort regulation (4) Peer learning (3) Help seeking (4) * Pintrich, P.R., Smith, D.A.F., Garcia, T., and McKeachie, W.J., 1991, NCRIPTL Report 91-B-004 Motivated Strategies for Learning Questionnaire * (MSLQ) used to investigate how aspects of the affective domain varied for students. MSLQ Instrument

Examples of Questions Comprising Subscales Self-Efficacy (one of the “Motivation” subscales) I believe I will receive an excellent grade in this class. I’m confident I can understand the basic concepts taught in this course. I’m certain I can understand the most difficult material presented in the readings for this course. I’m confident I can understand the most complex material presented by the instructor in this course. I’m confident I can do an excellent job on the assignments and tests in this course. I expect to do well in this class. I’m certain I can master the skills being taught in this class. Considering the difficulty of this course, the teacher, and my skills, I think I will do well in this class. GARNET: Geoscience Affective Research Network

Examples of Questions Comprising Subscales Time and Study Environment (one of the “Study Strategies” subscales) I usually study in a place where I can concentrate on my course work. I make good use of my study time for this course. I find it hard to stick to a study schedule. (REVERSED) I have a regular place set aside for studying. I make sure I keep up with the weekly readings and assignments for this course. I attend class regularly. I often find that I don’t spend very much time on this course because of other activities. (REVERSED) I rarely find time to review my notes or readings before an exam. (REVERSED). GARNET: Geoscience Affective Research Network

Students are scored separately on each of the 15 subscales, on a 7-point scale. GARNET: Geoscience Affective Research Network A high score on any of the subscales should, theoretically, enhance performance.

Which of the 15 MSLQ subscales significantly affect student performance? By how much? GARNET: Geoscience Affective Research Network

Method: Forward Stepwise Regression of MSLQ subscales against student performance (e.g. final grade) Multiple correlated regressors (X1-X4) make it difficult to tell which MSLQ subscale is the most significant contributor to student performance. We consider the significance of each MSLQ subscale individually, then test combinations of significant subscales. We can clearly see the individual contribution made by each MSLQ subscale to student performance. E.g. X 1 and X 4 are more influential to the student performance than X 2 and X 3.

Result of this Step-Wise Analysis: Model Equation for Student Score Score = (TS) +4.5(SE) -3.01(R) Significant MSLQ Subscales GARNET: Geoscience Affective Research Network

Result of this Step-Wise Analysis: Model Equation for Student Score Score = (TS) +4.5(SE) -3.01(R) The bigger this number, the more significance that subscale has. GARNET: Geoscience Affective Research Network

The average final score per class ranged from 70% to 90% In order to make valid comparisons across classes and institutions, we calculated each student’s percentile rank within his/her class. Average Score Class ID GARNET: Geoscience Affective Research Network

Our stepwise regression of the Pre-Course survey results yielded the following formula: Score = (TS) +4.5(SE) -3.01(R) SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal

GARNET: Geoscience Affective Research Network y = 0.086x % 10 20% 30 40% 50 60% 70 80% % 0%20%40%60%80%100% Model Score = (TS) +4.5(SE) -3.01(R) R 2 = 0.06 Pre-Course MSLQ Scores Correlated with Performance, Academic Year Actual Performance (Percentile Rank within Class) SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal Model Performance (Percentile Rank within Class)

GARNET: Geoscience Affective Research Network Our stepwise regression of the Post-Course survey results yielded the following formula: Score = (SE) +6.3(TS) -3.1(R) SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal

GARNET: Geoscience Affective Research Network Post-Course MSLQ Scores Correlated with Performance, Academic Year y = 0.227x % 10 20% 30 40% 50 60% 70 80% % 0%1020%3040%5060%7080%90100% Model Score = (SE) +6.3(TS) -3.1(R) R 2 = 0.23 SE = Self-Efficacy TS = Time and Study Environment R = Rehearsal Actual Performance (Percentile Rank within Class) Model Performance (Percentile Rank within Class)

Self-Efficacy Students with high self-efficacy are confident that they can Understand class material Do well on assignments and exams Master the skills taught in the course Model Score = (SE) +6.3(TS) -3.1(R) The factor that had the strongest correlation with performance was Self-Efficacy. GARNET: Geoscience Affective Research Network

Model Score = (SE) +6.3(TS) -3.1(R) Time and Study Environment Spend scheduled time studying in a place free of distractions Keep up with readings and assignments. Attend class regularly Students who score high on the time and study environment scale GARNET: Geoscience Affective Research Network

Model Score = (SE) +6.3(TS) -3.1(R) Rehearsal Students who score high on the rehearsal scale spend study time repeatedly Reciting items from lists Reading class notes and course readings Memorizing key words Rehearsal was negatively correlated with performance! GARNET: Geoscience Affective Research Network

Time and Study Environment GARNET: Geoscience Affective Research Network Pre Post Self Efficacy Rehearsal Changes in MSLQ Scores over the Semester Pre Post Pre Post These changes were exactly in the wrong direction! Top 25% Middle 50% Bottom 25%

IG EG TV CB SE TA RR EE OO CT MC TS ER PL HS Post-Course Correlations Among the 15 Scales of the MSLQ (Motivated Strategies for Learning Questionnaire) Strong Correlation Weak Correlation GARNET: Geoscience Affective Research Network

IG EG TV CB SE TA RR EE OO CT MC TS ER PL HS Self-Efficacy correlates strongly with Internal Goal Orientation Task Value Control of Learning Beliefs GARNET: Geoscience Affective Research Network

Intrinsic Goal Orientation Perceive learning tasks as ends in themselves, not just means to an end. Are motivated by challenge, curiosity, and a desire for mastery. Students who score high on the intrinsic goal orientation scale GARNET: Geoscience Affective Research Network

Task Value Like the subject matter of the course. Perceive the course material to be interesting, important and useful. Students who score high on the task value scale GARNET: Geoscience Affective Research Network

Control of Learning Beliefs Students who score high on the control of learning beliefs scale feel that their individual study efforts determine their academic performance. GARNET: Geoscience Affective Research Network

IG EG TV CB SE TA RR EE OO CT MC TS ER PL HS Time and Study Environment correlated strongly with Metacognitive Self-Regulation Effort Regulation GARNET: Geoscience Affective Research Network

Metacognitive Self-Regulation Students who score high on the metacognitive self-regulation scale plan, monitor and regulate their cognitive activities. They tend to… Stay focused in class and while studying Vary their study strategies with varying conditions Work to clear up confusions Ask themselves questions to check for understanding GARNET: Geoscience Affective Research Network

Effort Regulation Students who score high on the effort regulation scale persevere. They work hard, even when they feel lazy, are uninterested in the course material, or find the material to be difficult. GARNET: Geoscience Affective Research Network

Conclusions The MSLQ scores that are significantly correlated to student performance are – Self-Efficacy (positive correlation) – Time and Study Environment (positive correlation) – Rehearsal (negative correlation) Changes in MSLQ scores over the semester are in exactly the wrong direction. – Self-Efficacy decreases – Time and Study Environment decreases – Rehearsal increases Perhaps we can improve student performance by working to reverse these trends. GARNET: Geoscience Affective Research Network

Acknowledgements Thanks to NSF for funding this project Thanks to the 320 student participants who patiently completed the 80-question MSLQ twice and agreed to let us use their data. Special thanks to David McConnell for organizing the GARNET project. Special thanks to Jen Stempien for her awesome SAS psychotherapy skills. GARNET: Geoscience Affective Research Network